Local Path Planning Method for Unmanned Ship Based on Encounter Situation Inference and COLREGS Constraints

被引:3
|
作者
Wang, Gang [1 ,2 ]
Wang, Jingheng [3 ]
Wang, Xiaoyuan [1 ,2 ]
Wang, Quanzheng [1 ,2 ]
Chen, Longfei [1 ]
Han, Junyan [1 ]
Wang, Bin [1 ]
Feng, Kai [1 ,2 ]
机构
[1] Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266000, Peoples R China
[2] Intelligent Shipping Technol Innovat & Comprehens, Qingdao 266000, Peoples R China
[3] Ohio State Univ, Dept Math, Columbus, OH 43220 USA
关键词
encounter situation; COLREGS; unmanned ship; local path; planning; COLLISION-AVOIDANCE; SURFACE VEHICLE; ALGORITHM; OPTIMIZATION; GUIDANCE; SYSTEM;
D O I
10.3390/jmse12050720
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Local path planning, as an essential technology to ensure intelligent ships' safe navigation, has attracted the attention of many scholars worldwide. In most existing studies, the impact of COLREGS has received limited consideration, and there is insufficient exploration of the method in complex waters with multiple interfering ships and static obstacles. Therefore, in this paper, a generation method for a time-space overlapping equivalent static obstacle line for ships in multi-ship encounter scenarios where both dynamic and static obstacles coexist is proposed. By dynamically inferring ships' encounter situations and considering the requirements of COLREGS, the influence of interfering ships and static obstacles on the navigation of the target ship at different times in the near future is represented as static obstacle lines. These lines are then incorporated into the scene that the target ship encountered at the path planning moment. Subsequently, the existing path planning methods were extensively utilized to obtain the local path. Compared with many common path planning methods in random scenarios, the effectiveness and reliability of the method proposed are verified. It has been demonstrated by experimental results that the proposed method can offer a theoretical basis and technical support for the autonomous navigation of unmanned ships.
引用
收藏
页数:26
相关论文
共 50 条
  • [21] Local path optimization method for unmanned ship based on particle swarm acceleration calculation and dynamic optimal control
    Wang, Xiaoyuan
    Feng, Kai
    Wang, Gang
    Wang, Quanzheng
    APPLIED OCEAN RESEARCH, 2021, 110
  • [22] VFH plus Based Local Path Planning for Unmanned Surface Vehicles
    Wu, Chen-Fei
    Wang, Yu-Long
    Ma, Lang
    Rakic, Aleksandar
    IEEE INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SYSTEMS SCIENCE AND ENGINEERING (IEEE RASSE 2021), 2021,
  • [23] Trajectory planning for unmanned surface vehicles in multi-ship encounter situations
    Liu, Jianjian
    Chen, Huizi
    Xie, Shaorong
    Peng, Yan
    Zhang, Dan
    Pu, Huayan
    OCEAN ENGINEERING, 2023, 285
  • [24] Local Dynamic Obstacle Avoidance Path Planning Algorithm for Unmanned Vehicles Based on Potential Field Method
    Zhai L.
    Zhang X.
    Zhang X.
    Wang C.
    Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 2022, 42 (07): : 696 - 705
  • [25] Collision avoidance path planning in multi-ship encounter situations
    Yu-Tao Kang
    Wei-Jiong Chen
    Da-Qi Zhu
    Jin-Hui Wang
    Journal of Marine Science and Technology, 2021, 26 : 1026 - 1037
  • [26] Collision avoidance path planning in multi-ship encounter situations
    Kang, Yu-Tao
    Chen, Wei-Jiong
    Zhu, Da-Qi
    Wang, Jin-Hui
    JOURNAL OF MARINE SCIENCE AND TECHNOLOGY, 2021, 26 (04) : 1026 - 1037
  • [27] A COLREGs-based path-planning method for collision avoidance considering path cost through reinforcement learning
    Song, Wanping
    Chen, Zengqiang
    Sun, Mingwei
    Wang, Yongshuai
    Sun, Qinglin
    OCEAN ENGINEERING, 2025, 325
  • [28] Multi-ship encounter situation adaptive understanding by individual navigation intention inference
    Wang, Shaobo
    Zhang, Yingjun
    Zheng, Yisong
    OCEAN ENGINEERING, 2021, 237
  • [29] Complex encounter situation modeling and prediction method for unmanned ships based on bounded rational game
    Wang, Gang
    Wang, Xiaoyuan
    Wang, Quanzheng
    Chen, Longfei
    Han, Junyan
    Wang, Bin
    Shi, Huili
    OCEAN ENGINEERING, 2023, 273
  • [30] Research on Local Path Planning Algorithm for Unmanned Vehicles
    Peng X.
    Xie H.
    Huang J.
    Qiche Gongcheng/Automotive Engineering, 2020, 42 (01): : 1 - 10